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omicverse/single_cell_tutorial ★ 309 44 DATA_RESEARCH

This repository is an educational tutorial for single-cell sequencing analysis best practices using Python. It provides a structured series of Jupyter notebooks and documentation covering preprocessing, quality control, normalization, feature selection, and advanced topics like trajectory inference and multi-modal data analysis. The tutorial uses real-world example datasets (e.g., 10x Multiome) and emphasizes reproducible workflows with AnnData and MuData objects, leveraging libraries such as scanpy, omicverse, and scverse tools. While primarily educational, it demonstrates standard data analysis patterns that can be adapted for similar single-cell projects.

RATING: 7.1/10 REPRO: 7.5/10 MAINT: maintained DRIFT: medium
#single-cell #preprocessing #anndata #mudata #scanpy #omics
▸ 1 reusable components found
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